Computer languages of the future will be more concerned with goals and less with procedures specified by the programmer.
Our present culture may be largely shaped by this strange idea of isolating children’s thought from adult thought. Perhaps the way our culture educates its children better explains why most of us come out as dumb as they do, than it explains how some of us come out as smart as they do.
Everything is similar if you’re willing to look far out of focus.
In science, one learns the most by studying what seems to be the least.
Experience has shown that science frequently develops most fruitfully once we learn to examine the things that seem the simplest, instead of those that seem the most mysterious.
We wanted to solve robot problems and needed some vision, action, reasoning, planning, and so forth. We even used some structural learning, such as was being explored by Patrick Winston.
Everything, including that which happens in our brains, depends on these and only on these: A set of fixed, deterministic laws.
But just as astronomy succeeded astrology, following Kepler’s discovery of planetary regularities, the discoveries of these many principles in empirical explorations of intellectual processes in machines should lead to a science, eventually.
By the way, it was his simulations that helped out in Jurassic Park – without them, there would have been only a few dinosaurs. Based on his techniques, Industrial Light and Magic could make whole herds of dinosaurs race across the screen.
I believed in realism, as summarized by John McCarthy’s comment to the effect that if we worked really hard, we’d have an intelligent system in from four to four hundred years.
There was a failure to recognize the deep problems in AI; for instance, those captured in Blocks World. The people building physical robots learned nothing.
Once the computers got control, we might never get it back. We would survive at their sufferance. If we’re lucky, they might decide to keep us as pets.
Common sense is not a simple thing. Instead, it is an immense society of hard-earned practical ideas – of multitudes of life-learned rules and exceptions, dispositions and tendencies, balances and checks.
When David Marr at MIT moved into computer vision, he generated a lot of excitement, but he hit up against the problem of knowledge representation; he had no good representations for knowledge in his vision systems.
We must see that music theory is not only about music, but about how people process it. To understand any art, we must look below its surface into the psychological details of its creation and absorption.
To say that the universe exists is silly, because it says that the universe is one of the things in the universe. So there’s something wrong with questions like, “What caused the Universe to exist?”
Papert’s Principle: Some of the most crucial steps in mental growth are based not simply on acquiring new skills, but on acquiring new administrative ways to use what one already knows.
But, somehow, I have got to make both of these things just and right to me. I have got to make everything that has happened to me good for me. The plank bed, the loathsome food, the hard ropes, the harsh orders, the dreadful dress that makes sorrow grotesque to look at, the silence, the solitude, the shame – each and all of these things I had to transform into a spiritual experience. There is not a single degradation of the body which I must not try and make into a spiritualizing of the soul.
Each of our major Ways to Think results from turning certain resources on while turning certain others off – and thus changing some ways that our brains behave.
The art of a great painting is not in any one idea, nor in a multitude of separate tricks for placing all those pigment spots, but in the great network of relationships among its parts. Similarly, the agents, raw, that make our minds are by themselves as valueless as aimless, scattered daubs of paint. What counts is what we make of them.